Showing papers by "Peng Shi published in 2007"

Fault Detection for Uncertain Fuzzy Systems: An LMI Approach

Abstract: This paper studies the problem of designing a robust fault-detection system for uncertain Takagi-Sugeno fuzzy models. The worst case fault sensitivity measure is formulated in terms of linear matrix inequalities. The existence of a robust fault detection system that guarantees i) the L2-gain from a fault signal to a residual signal greater than a prescribed value and ii) the L2-gain from an exogenous input to a residual signal less than a prescribed value is given in terms of the solvability of linear matrix inequalities. Numerical examples are used to illustrate the effectiveness of the proposed design techniques.

H/sub /spl infin// fault detection filter design for networked control systems modelled by discrete Markovian jump systems

Abstract: This paper deals with the design of robust fault detection for networked control systems with large transfer delays, in which it is impossible to totally decouple the fault effects from unknown inputs (including model uncertainties and external plant disturbances). First, we employ the multirate sampling method together with the augmented state matrix method to model the long random delay networked control systems as Markovian jump systems. Then, a Hinfin fault detection filter is designed based on the model developed. Through the appropriate choice of the filter gain, the filter is convergent if there is no disturbance in the system, meanwhile the effect of disturbances on the residual will satisfy a prescribed Hinfin performance. The problem of achieving satisfactory sensitivity of the residual to fault is formulated and its solution is given. Finally, a numerical example is presented to illustrate the effectiveness of the proposed techniques.

Active disturbance rejection control for uncertain multivariable systems with time-delay

Abstract: A new nonlinear control method for multivariable systems with time delay is presented. It is based on a unique active disturbance rejection concept. The proposed active disturbance rejection controller (ADRC) consists of the tracking differentiator, the extended state observer and the nonlinear proportional derivative (PD) controller. In this approach, the systems with time delay in the input are viewed as higher-order systems without time delay in the input, the approximation error between the nominal systems and real systems and other uncertainties, all of which are seen as `disturbance' by ADRC and are actively compensated. The techniques developed here can be effectively used in engineering systems, such as chemical processes, and this is demonstrated by an example.

$H_\infty$ Filtering of Discrete-Time Switched Systems With State Delays via Switched Lyapunov Function Approach

Abstract: In this note, the problem of Hinfin filtering for a class of discrete-time switched systems with state delays is investigated. Attention is focused on the design of a stable filter guaranteeing a prescribed noise attenuation level in the Hinfin sense. By using switched Lyapunov functionals, sufficient conditions for the solvability of this problem are obtained in terms of linear matrix inequalities (LMIs), by solving which a desired Hinfin filter can be constructed. A numerical example is provided to demonstrate the effectiveness of the proposed techniques.

Robust Output Feedback Tracking Control for Time-Delay Nonlinear Systems Using Neural Network

Abstract: In this paper, the problem of robust output tracking control for a class of time-delay nonlinear systems is considered. The systems are in the form of triangular structure with unmodeled dynamics. First, we construct an observer whose gain matrix is scheduled via linear matrix inequality approach. For the case that the information of uncertainties bounds is not completely available, we design an observer-based neural network (NN) controller by employing the backstepping method. The resulting closed-loop system is ensured to be stable in the sense of semiglobal boundedness with the help of changing supplying function idea. The observer and the controller designed are both independent of the time delays. Finally, numerical simulations are conducted to verify the effectiveness of the main theoretic results obtained

Novel robust stability criteria for uncertain stochastic Hopfield neural networks with time-varying delays

Abstract: The problem of stochastic robust stability of a class of stochastic Hopfield neural networks with time-varying delays and parameter uncertainties is investigated in this paper. The parameter uncertainties are time-varying and norm-bounded. The time-delay factors are unknown and time-varying with known bounds. Based on Lyapunov–Krasovskii functional and stochastic analysis approaches, some new stability criteria are presented in terms of linear matrix inequalities (LMIs) to guarantee the delayed neural network to be robustly stochastically asymptotically stable in the mean square for all admissible uncertainties. Numerical examples are given to illustrate the effectiveness and less conservativeness of the developed techniques.

Robust l2-l filtering for switched linear discrete time-delay systems with polytopic uncertainties

Abstract: The problem of robust l2-linfin filtering for switched linear discrete-time systems with polytopic uncertainties and time-varying delays is investigated. The time delay is assumed to be time-varying and bounded, which covers constant delay and mode-dependent constant delays as special cases. A robust switched linear filter is designed based on the mode-switching idea and a parameter-dependent stability approach such that the corresponding filtering error system is robustly asymptotically stable and achieves a prescribed l2-l infin performance index for all admissible uncertainties. The existence conditions for such a filter, dependent on the upper and lower bounds of time-varying delays, are formulated in terms of a set of linear matrix inequalities. By solving that corresponding convex optimisation problem, the desired filter is obtained and an optimal l 2-linfin noise-attenuation level bound of the resulting filtering error system is guaranteed as well. A numerical example is given to show the feasibility and potential of the theoretical results

Adaptive Variable Structure and Commanding Shaped Vibration Control of Flexible Spacecraft

Abstract: In this paper, a new approach for vibration control of flexible spacecraft during attitude maneuvering is proposed. This control strategy integrates the command input shaping and the technique of dynamic variable structure output feedback control. More precisely, the input shaper is implemented outside of the feedback loop, which is designed for the reference model to achieve the exact elimination of residual vibration by modifying the existing command; whereas for the feedback loop, the controller is designed to make the closed-loop system follow the reference model with input shaper and eliminate the residual vibrations in the presence of parametric uncertainty and external disturbances. An attractive feature of this proposed dynamic variable structure output feedback control algorithm is that the parametric uncertainties of the system are not necessarily to satisfy the so-called matching condition or invariance conditions, provided that certain bounds are known. Furthermore, an adaptive version of the proposed controller is achieved through releasing the limitation of knowing the bounds of the uncertainties and perturbations in advance. The adaptive control law results in substantially simpler stability analysis and improves overall response. Compared with conventional methods, the developed control scheme guarantees not only the stability of the closedloop system, but also yields better performance and robustness in the presence of parametric uncertainties and external disturbance. Simulation results are presented for the spacecraft model to show the effectiveness of the proposed control techniques.

New stability and stabilization conditions for systems with time-delay

Abstract: In this article, the problems of stability and stabilization for systems with both constant and time-varying delays have been considered. By the so-called lifting method, time-delay systems are transformed into delay-free systems such that simple necessary and sufficient conditions have been developed for the stability analysis of systems with constant delays. For systems with time-varying delays, they have been converted to a switched system so that the existing results can be applied to analyze the problems of stability and stabilization. Linear matrix inequality (LMI) approach has been employed to the state feedback control design. Numerical examples are given to show the effectiveness of the proposed technique.

Sliding mode control of uncertain linear discrete time systems with input delay

Abstract: The problem of sliding-mode control is investigated for a class of uncertain linear systems with input-delay in discrete time. First, a predictor in discrete time is introduced, which converts the original system with input delay to an equivalent system without the explicit appearance of time delay and makes the control problem solvable. Then, sliding-mode controls are constructed for both systems with and without bounded disturbance. Simulation studies show the effectiveness of the control scheme.

Nonlinear dynamics and stability analysis of vehicle plane motions

Abstract: In this article, the problems of dynamics and stability for vehicle planar motion systems have been investigated. By introducing a so-called joint-point locus approach, equilibria of the system and their associated stability properties are given geometrically. With this method, it is discovered that the difference between the front and the rear steering angles plays a key role in vehicle system dynamics and that the topological structure of the phase portrait and the types of bifurcations are different from those published previously. In particular, the vehicle system could still be stabilized even when pushed to work in a certain severely nonlinear region, by applying extremely large steering angles. However, it is worth noticing that the attractive domain of the stable equilibrium is very narrow. These developments might prove to be important in active steering control design. Numerical experiments are carried out to illustrate the potentials of the proposed techniques.

H ∞ output-feedback control for switched linear discrete-time systems with time-varying delays

Abstract: In this paper, the problem of H ∞ output feedback control for switched linear discrete-time systems with time delays is investigated. The time delay is assumed to be time-varying and bounded. By constructing a switched quadratic Lyapunov function for the underlying system, both static and dynamic H ∞ output feedback controllers are designed respectively such that the corresponding closed-loop system under arbitrary switching signals is asymptotically stable and a prescribed H ∞ noise-attenuation level bound is guaranteed. A cone complementary linearization algorithm is exploited to design the controllers. A numerical example is presented to show the effectiveness of the developed theoretical results.

Delay-dependent h/spl infin/ filtering for uncertain time delay nonlinear systems: an lmi approach

Abstract: The problem of designing a delay-dependent robust Hinfin filter for time delay Takagi-Sugeno fuzzy models is considered. The purpose is to design delay-dependent Hinfin filters ensuring a prescribed Hinfin performance level for the estimation error, irrespective of the uncertainties and the time delays. Sufficient conditions for the existence of a delay-dependent Hinfin filter are given in terms of linear matrix inequalities. Membership functions' (MFs) structural information is incorporated into the delay-dependent filter design to reduce the conservativeness of neglecting this information. It is shown that incorporating MFs' structural information into the filter design does not lead to bilinear matrix inequalities, as in the control design case. Finally, a numerical example is used to illustrate the effectiveness of the proposed design techniques.

Adaptive Observer-Based Fault Diagnosis with Application to Satellite Attitude Control Systems

Abstract: In this paper, a novel adaptive approach for fault diagnosis is proposed. In order to enhance performance of fault estimation, the proposed fault estimator is composed of proportional term and integral one, which enables to improve rapidity and accuracy for fault estimation. Finally, a satellite attitude control example is presented to illustrate the efficiency of the presented techniques for fault diagnosis.

Delay‐dependent filtering design for time‐delay systems with Markovian jumping parameters

Abstract: Two filtering problems—H∞ filtering and H2 filtering—for the linear Markovian jump systems with time delay are considered in this paper. The proposed new filtering approach guarantees that the results are less conservative than that obtained by other existing approaches. Numerical example well demonstrates the proposed algorithms.

Gain-scheduled stabilisation of linear parameter-varying systems with time-varying input delay

Abstract: This paper deals with the problem of gain-scheduled stabilisation for linear parameter-varying systems with time-varying input delay. New delay-dependent criteria are developed based on the reduction method combined with the parameter-dependent Lyapunov approach. Sufficient conditions are presented to design gain-scheduled controllers to stabilise the closed-loop systems from past input information in terms of parameterised linear matrix inequalities (LMI). One numerical example is provided to demonstrate the effectiveness of the proposed methods.

A New Approach to Robust H∞ Filtering for Uncertain Systems with Both Discrete and Distributed Delays

Abstract: This paper is concerned with robust H∞ filter design for a class of linear distributed delay systems with norm-bounded time-varying parameter uncertainties. The distributed delays are assumed to appear in both state and measurement equations. A new design method is proposed by introducing some relaxation matrices and tuning parameters, which can be chosen properly to lead to a less conservative result. A sufficient condition is obtained to guarantee the existence of desired H∞ filters, which can be constructed by solving a convex optimization problem. A numerical example is included to illustrate the effectiveness and the reduced conservatism of the proposed design technique.

Delay-Dependent Stabilization of LPV Systems with Time-Varying Input Delay

Abstract: This paper addresses the problem of delay-dependent stabilization for linear parameter-varying systems with time-varying input delay. A new delay-dependent criterion is developed by constructing the reduction method and combining with the parameter-dependent Lyapunov approach. Sufficient conditions are presented to design gain-scheduled controller to stabilize the closed-loop systems from past input information in terms of parameterized linear matrix inequalities.

New upper solution bounds for perturbed continuous algebraic Riccati equations applied to automatic control

Abstract: In dynamical systems studies, the so-called Riccati and Lyapunov equations play an important role in stability analysis, optimal control and filtering design. In this paper, upper matrix bounds for the perturbation of the stabilizing solution of the continuous algebraic Riccati equation (CARE) are derived for the case when one, or all the coefficient matrices are subject to small perturbations. Comparing with existing works on this topic, the proposed bounds are less restrictive. In addition to these bounds, iterative algorithms are also derived to obtain more precise estimates.

Resilient feedback stabilization of discrete-time systems with delays

Abstract: A class of linear, uncertain discrete-time systems with state delay is considered. We develop an linear matrix inequality (LMI)-based analysis and redesign procedures for improved robust stability of discretetime systems with state delay and bounded nonlinearities. Then, we address the robust stabilization using nominal and resilient feedback designs. In both cases, the trade-off between the size of the controller gains and the bounding factors is illuminated and incorporated into the design formalism. Seeking computational convenience, all the developed results are cast in the format of LMIs and several numerical examples are presented throughout the paper.

New global asymptotic stability criterion for neural networks with discrete and distributed delays

Abstract: This paper investigates the problem of global asymptotic stability for a class of neural networks with time-varying and distributed delays. By the Lyapunov-Krasovskii functional approach, a new delay-dependent stability criterion is derived in terms of linear matrix inequalities (LMIs). The new stability condition does not require the time delay function to be continuously differentiable and its derivative to be less than 1, and it allows the time delay to be a fast time-varying function. Simulation examples are given to demonstrate the effectiveness of the developed techniques.

ℋ∞ Filter for Uncertain Markovian Jump Nonlinear Systems: An LMI Approach

Abstract: The paper addresses the problem of designing a robust filter for a class of uncertain Markovian jump nonlinear systems described by a Takagi–Sugeno fuzzy model with Markovian jumps. LMI-based sufficient conditions for the existence of a robust filter that guarantees the ℒ2-gain from an exogenous input to an estimation error to be less than a prescribed value are derived. A tunnel diode circuit is used to illustrate the effectiveness of the proposed design techniques.

Asymptotic stability in the distribution of nonlinear stochastic systems with semi-markovian switching

Abstract: In this paper, finite phase semi-Markov processes are introduced. By introducing variables and a simple transformation, every finite phase semi-Markov process can be transformed to a finite Markov chain which is called its associated Markov chain. A consequence of this is that every phase semi-Markovian switching system may be equivalently expressed as its associated Markovian switching system. Existing results for Markovian switching systems may then be applied to analyze phase semi-Markovian switching systems. In the following, we obtain asymptotic stability for the distribution of nonlinear stochastic systems with semi-Markovian switching. The results can also be extended to general semi-Markovian switching systems. Finally, an example is given to illustrate the feasibility and effectiveness of the theoretical results obtained.

H∞ filtering for uncertain bilinear stochastic systems

Abstract: This paper is concerned with the problem of H ∞ filtering for continuous-time uncertain stochastic systems. The model under consideration contains both state-dependent stochastic noises and deterministic parameter uncertainties residing in a polytope. According to the online availability of the information on the uncertain parameters, we propose two approaches, namely robust stochastic H ∞ filtering and parameter-dependent stochastic H ∞ filtering. Both approaches solve the filtering problems based on a modified (improved) bounded real lemma for continuous-time stochastic systems, which decouples the product terms between the Lyapunov matrix and systems matrices and enables us to exploit parameter-dependent stability idea in the filter designs. Sufficient conditions for the existence of admissible robust stochastic H ∞ filters and parameter-dependent stochastic H ∞ filters are obtained in terms of linear matrix inequalities, upon which the filter designs are cast into convex optimization problems. Since the filter designs make full use of the parameter-dependent stability idea, the obtained results are less conservative than the existing one in the quadratic framework. A numerical example is provided to illustrate the effectiveness and advantage of the filter design methods proposed in this paper.

Robust Stability of Uncertain Cellular Neural Networks with Time-Varying Delays

Abstract: Grid computing is increasingly being viewed as the next phase of distributed computing. In this paper we propose a new replica replacement strategy, called JARRS (shorts for job-attention replica replacement strategy), which applies for replica management in data grids. A novel interpretation of locality appropriate for grid is presented. It is the grid locality that lays foundation of replica replacement strategy. A new approach, file forward-looking, is suggested. JARRS uses file forward-looking and references to recently accessed files to make decision. Experiments show that JARRS has a better efficiency and robust property for different file access patterns than others.

Robust Stability Criteria for Uncertain Stochastic Cellular Neural Networks with Time Delays

Abstract: In this paper, the global robust asymptotic stability problem is considered for stochastic cellular neural networks with time delays and parameter uncertainties The aim of this paper is to establish easily verifiable conditions under which the stochastic cellular neural networks is globally robustly asymptotically stable in the mean square for all admissible parameter uncertainties Base on Lyapunov- Krasovskii functional and stochastic analysis approaches, a linear matrix inequality (LMI) approach is developed to derive the stability criteria A numerical example is provided to illustrate the effectiveness and applicability of the proposed criteria

Robust Parameter-Dependent Constrained Model Predictive Control

Abstract: The problem of robust constrained model predictive control (MFC) of systems with polytopic uncertainty is considered in this paper. New sufficient conditions for the existence of parameter-dependent Lyapunov functions are proposed in terms of linear matrix inequalities (LMIs), which will reduce the conservativeness resulting from using a single Lyapunov function. At each sampling instant, the corresponding parameter-dependent Lyapunov function is an upper bound for a worst-case objective function, which can be minimized using the LMI convex optimization approach. Based on the solution of optimization at each sampling instant, the corresponding state feedback controller is designed, which can guarantee that the resulting closed-loop system is robustly asymptotically stable. In addition, the feedback controller will meet the specifications for systems with input or output constraints, for all admissible time-varying parameter uncertainties. Numerical examples are presented to demonstrate the effectiveness of the proposed techniques.